Question 1

How do I get started?

Accepted Answer

Contact us to book a demo to see the platform in action as well as access to our SDK and developer documentation.

Question 2

What is Edge AI and how is this platform different?

Accepted Answer

Our platform delivers a complete stack for real-time, on-device AI — including graph-based execution (EdgeCore), ML runtimes (Edge AI/ML), LLM inference (EdgeInfer), agent orchestration (EdgeAgent), and a no-code UI (EdgeStudio). Unlike cloud-first solutions, we're ultra optimized for low-latency, privacy, and safety at the edge.

Question 3

Can I run the Edge AI platform on the cloud?

Accepted Answer

Our platform is scalable to build hybrid edge-cloud workflows through integration into your existing stack. Whether you're connecting to cloud APIs, syncing inference results, or deploying alongside your existing infrastructure, we can provide hands-on support to help you integrate seamlessly. If you're building a custom cloud-to-edge pipeline, we'll work directly with your team to bridge deployment, dataflow, and monitoring needs.

Question 4

What hardware and OS does your runtime support?

Accepted Answer

Our runtime is portable across most hardware vendors and operating systems, including macOS, Windows, and Linux. We support deployment on embedded devices, automotive-grade systems, industrial PCs, and more — with a safety-qualified variant available for regulated environments.

Question 5

Do you support safety-critical deployments?

Accepted Answer

Yes. Edge SC is our safety-qualified runtime designed to meet standards like ISO 26262, IEC 61508, or DO-178C — suitable for automotive, aerospace, robotics, and industrial use cases.

Question 6

What's the difference between Edge AI/ML and EdgeInfer?

Accepted Answer

Edge AI/ML handles traditional ML models such as vision, detection, segmentation, and sensor fusion. EdgeInfer is built specifically for running LLMs, embedding, and re-ranking models on-device.

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